In this paper, a new automatic and adaptive aircraft target detection algorithm in high-resolution airport synthetic aperture radar (SAR) images is proposed. Firstly, region segmentation is used to detect the apron area in the images, which provides the potential area where aircrafts may exist and reduce the search range. Secondly, upon the apron area the pre-segmentation is taken to label the possible target points. Thirdly, the constant false alarm rate (CFAR) detector is improved to cope with multi-target detection situation. The clutter pixels in the sliding detection window will be removed automatically based on pre-segmentation result. As a result, more structural features of the targets are preserved. At last, in order to eliminate the detected false targets and solve the problem that the same target is divided into several disconnected areas, a new joint algorithm based on the area recognition factors and distance cluster is presented. The real airborne SAR image data of some airport is used to verify this target detection algorithm, and the result indicates that this algorithm can detect the aircraft target precisely and decrease the false alarm rate.
This letter mainly aims at an E-Centrist descriptor for the pedestrian recognition in image sequences with background
moving slowly. Utilizing the motion information detected from the image sequences, pedestrian recognition algorithm is
implemented by combining region of interest（ROI）which probably includes potential pedestrians and an enhanced
descriptor from contour. Experimental results demonstrate that the presented method improves the speed as well as the
accuracy of pedestrian recognition in test sequences.
An efficient automatic small target detection algorithm in infrared image is proposed. Based on non-linear histogram equalization, a coarse-to-fine segmentation is used to segment IR image into target candidates.
Then genuine targets are captured by using contrast-based confidence measure and empirical size constraint. Experimental results demonstrate that the presented method is efficient, accurate and robust.